Citation: M. Müller-Linow (2018-08-01): Estimating leaf area with the new smartphone app Plant Screen Mobile_ image data and corresponding ground truth measurements from a case study in Banana and Eragrostis. DOI:10.25622/FZJ/2018/1
Abstract: Leaf area is one of the fundamental variables to quantify plant growth and physiological function and is therefore widely used to characterize genotypes and their interaction with the environment. We developed a smartphone app (PSM) to estimate projected leaf area (PLA), which is a good proxy for leaf area and biomass. The core of the application comprises different classification approaches to distinguish between foreground (plants or other targets) and background. We tested our approach in two case studies with banana and Eragrostis spec. and compared PLA results to ground truth data of leaf area and fresh weight. Using the same plants we also measured PLA with our SCREENHOUSE system. The SCREENHOUSE imaging system of IBG-2 is an automated greenhouse plant phenotyping platform, equipped with an imaging station for data acquisition under controlled light conditions. It is equipped with three RGB cameras (Grasshopper 2, Point Grey Research, 5MP) that image plants from three different view angles. Support vector machine (SVM) classification of foreground and background pixels is a supervised approach based on training data sets, which generally yields very good solutions for linear- and nonlinear separable data regarding stability and accuracy and which is robust against outliers in the data. The two genotypes of banana plantlets were obtained from University of Hohenheim - Institute of Crop Science (Crop Physiology of Specialty Crops), Germany. Khai Thong Ruang KTR (Musa AAA) is a drought-sensitive desert banana from Thailand, Saba (Musa ABB) is a drought-tolerant African plantain. In total we used 52 replicates, 27 KTR and 25 Saba. In the Eragrostis experiment we used two species, i.e. 100 replicates in Eragrostis tef (teff) and 40 replicates in Eragrostis pilosa. Each plant was imaged from 4 sides adding up to 208 images in banana and 560 images in Eragrostis. Projected leaf area (averaged over 4 views) was estimated with PSM and compared against SVM-classified images that were acquired and analyzed with the SCREENHOUSE imaging system. For the destructive measurements plant leaves where weighed with a high-accuracy lab balance (XS 205, Mettler Toledo, United States) and measured with a leaf area meter (LI-3100, Licor, United States) to obtain the true leaf area destructively. The data comes with a txt-file, which describes the experiment, the data folder structure and the imaging systems. The image collection contains the smartphone and SCREENHOUSE data. The SCREENHOUSE images come with image masks that were computed with support vecor machine classificaition. The PSM projected leaf area was computed with the ExGR greenness method using a threshold of 0.03 for Banana and -0.03 for Eragrostis. The data is completed by the destructive weight and leaf area measurements.
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Tobias Wojciechowski, Fabio Fiorani [Show full information]
Mark Müller-Linow [Show full information]
|PUBLISHER:||Forschungszentrum Jülich GmbH, Jülich, Wilhelm-Johnen-Straße, 52428, Germany|
|SUBJECT:||Plant image segmentation, Image analysis, Mobile Application, Android, Projected Leaf Area|